Python使用ctypes访问C代码

工具：CodeBlocks

新建一个分享库工程( Shared library )，随便编写一个C代码的函数

// test.c

#include <stdio.h>

int fib(int n)
{
    if( n ==  || n == )
    {
        return ;
    }
    else
    {
        return fib(n-) + fib(n-);
    }
}

编译，在bin/Debug/目录中生成libtest.dll动态链接库文件，该文件可以通过ctypes模块进行访问使用，在该文件目录下新建一个test.py文件

# test.py

import ctypes
import os

_file_path = os.path.join(os.path.dirname(__file__), 'libtest.dll')
_mod = ctypes.cdll.LoadLibrary(_file_path)   #加载动态库文件，返回一个类对象 <class 'ctypes.CDLL'>

# int fib(int n)
fib = _mod.fib               #获取类方法
fib.argtypes = (ctype_int,)  #配置参数类型（tuple）
fib.restype = ctypes_int     #配置返回值类型

#现在可以直接使用fib函数了
for i in range(10):
    print( fib(i), end=' ' )

---

C函数的指针作为参数情况

// 参数有指针的函数
int divide(int a, int b, int *remainder) {
    int quot = a / b;
    *remainder = a % b;
    return quot;
}

---

# 相应的处理办法

# int divide(int, int, int *)
_divide = _mod.divide
_divide.argtypes = (ctypes.c_int, ctypes.c_int, ctypes.POINTER(ctypes.c_int))
_divide.restype = ctypes.c_int

def divide(x, y):
　　rem = ctypes.c_int()
　　quot = _divide(x, y, rem)
　　return quot,rem.value

---

C函数的数组作参数的情况

double avg(double *a, int n) {
    int i;
    double total = 0.0;
    for (i = ; i < n; i++) {
        total += a[i];
    }
    return total / n;

# 对于C中的数组，Python中没有固定的对应类型，所以要分类处理：
# Define a special type for the 'double *' argument
class DoubleArrayType:
    def from_param(self, param):            #对传进来的参数进行分发
        typename = type(param).__name__
        if hasattr(self, 'from_' + typename):
            return getattr(self, 'from_' + typename)(param)
        elif isinstance(param, ctypes.Array):
            return param
        else:
            raise TypeError("Can't convert %s" % typename)

    # Cast from array.array objects
    def from_array(self, param):
        if param.typecode != 'd':
            raise TypeError('must be an array of doubles')
        ptr, _ = param.buffer_info()
        return ctypes.cast(ptr, ctypes.POINTER(ctypes.c_double))

    # Cast from lists/tuples
    def from_list(self, param):
        val = ((ctypes.c_double)*len(param))(*param)
return val

    from_tuple = from_list

    # Cast from a numpy array
    def from_ndarray(self, param):
        return param.ctypes.data_as(ctypes.POINTER(ctypes.c_double))

DoubleArray = DoubleArrayType()
_avg = _mod.avg
_avg.argtypes = (DoubleArray, ctypes.c_int)
_avg.restype = ctypes.c_double

def avg(values):
    return _avg(values, len(values))